mengqidyangge Goto Github PK

sgan

Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018

simple-faster-rcnn-pytorch

A simplified implemention of Faster R-CNN that replicate performance from origin paper

slip

Code release for SLIP Self-supervision meets Language-Image Pre-training

softteacher

Semi-Supervised Learning, Object Detection, ICCV2021

star

Code for "Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction"

stgat

STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction

tood

TOOD: Task-aligned One-stage Object Detection, ICCV2021 Oral

towards-realtime-mot

Joint Detection and Embedding for fast multi-object tracking

tracking_wo_bnw

Implementation of "Tracking without bells and whistles” and the multi-object tracking "Tracktor"

trajectron

Code accompanying "The Trajectron: Probabilistic Multi-Agent Trajectory Modeling with Dynamic Spatiotemporal Graphs" by Boris Ivanovic and Marco Pavone.

transt

Transformer Tracking (CVPR2021)

transtrack

Multiple-Object Tracking with Transformer

tubetk

Official implementation of paper: TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model (CVPR 2020 oral)

ucas-course

**科学院大学研一课程课件共享项目University of Chinese Academy of Sciences postgraduate course textbook sharing project

ucas_courses

all courses' homework

uvlp

CVPR 2022 (Oral) Pytorch Code for Unsupervised Vision-and-Language Pre-training via Retrieval-based Multi-Granular Alignment

video_captioning_rl

Code and Models for paper "Reinforced Video Captioning with Entailment Rewards (EMNLP 2017)"

vissl

VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.

weightstandardization

Standardizing weights to accelerate micro-batch training

x-vlm

X-VLM: Multi-Grained Vision Language Pre-Training (ICML 2022)

yolov3_pytorch_ros

Real-time object detection with ROS, based on YOLOv3 and PyTorch

zero-shot-detection-via-vision-and-language-knowledge-distillation

zsgnet-pytorch

Official implementation of ICCV19 oral paper Zero-Shot grounding of Objects from Natural Language Queries (https://arxiv.org/abs/1908.07129)